According to Phythian, DataOps is forecasted to be one of the top 7 Big Data Analytics trends in 2019. DataOps is a new data analytics technology in the modern digital world. Some feel DataOps is nothing but DevOps for data but it is even beyond that. In simple terms, you combine DevOps with data analytics to get DataOps. DataOps applies Agile and DevOps methods to the entire data analytics lifecycle. Though DevOps is not in the top list, it does not mean that DevOps has lost its flavor and not widely adopted. As Gartner predicted DevOps is growing exponentially with many enterprises adopting them at a faster pace in their Agile transformation. DevOps ensures seamless collaboration between developers, Testing and IT Ops admins while DataOps does the same including Data operators and Data consumers. As DevOps focuses on automating the entire pipeline of continuous integration, continuous delivery and continuous deployment, DataOps orchestrates monitors and manages the entire data pipeline deploying new analytics into the overall pipeline.
The cloud migrations have become slow with the increasing amount of data volume which further adds more complexities to manage the different data elements but DataOps strengthens the Enterprise Data Value Chain and overcome the current challenges. The paper will highlight how DataOps compliments DevOps and does not eradicate DevOps. Suresh will detail how sensitive data can be governed effectively ensuring compliance with GDPR, HIPAA and other regulations.